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<div class="section" id="usage">
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<h1>Usage<a class="headerlink" href="#usage" title="Permalink to this headline">¶</a></h1>
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<p>First of all, you need to install the package. See <a class="reference internal" href="installation.html"><span class="doc">Installation</span></a> for installation instructions.</p>
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<div class="section" id="simulation-settings">
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<h2>Simulation Settings<a class="headerlink" href="#simulation-settings" title="Permalink to this headline">¶</a></h2>
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<p>Once installed, before running a simulation, you need to configure it.</p>
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<ul>
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<li><p class="first">In the settings.py file you will find the configuration of the network.</p>
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<div class="code python highlight-default"><div class="highlight"><pre><span></span><span class="c1"># Network settings</span>
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<span class="n">network_type</span> <span class="o">=</span> <span class="mi">1</span>
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<span class="n">number_of_nodes</span> <span class="o">=</span> <span class="mi">1000</span>
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<span class="n">max_time</span> <span class="o">=</span> <span class="mi">50</span>
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<span class="n">num_trials</span> <span class="o">=</span> <span class="mi">1</span>
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<span class="n">timeout</span> <span class="o">=</span> <span class="mi">2</span>
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</pre></div>
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</div>
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</li>
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<li><p class="first">In the Simulation Settings JSON file, you will find the configuration of the models.</p>
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</li>
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</ul>
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</div>
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<div class="section" id="network-types">
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<h2>Network Types<a class="headerlink" href="#network-types" title="Permalink to this headline">¶</a></h2>
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<p>There are three types of network implemented, but you could add more.</p>
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<div class="code python highlight-default"><div class="highlight"><pre><span></span><span class="k">if</span> <span class="n">settings</span><span class="o">.</span><span class="n">network_type</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
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<span class="n">G</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">complete_graph</span><span class="p">(</span><span class="n">settings</span><span class="o">.</span><span class="n">number_of_nodes</span><span class="p">)</span>
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<span class="k">if</span> <span class="n">settings</span><span class="o">.</span><span class="n">network_type</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
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<span class="n">G</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">barabasi_albert_graph</span><span class="p">(</span><span class="n">settings</span><span class="o">.</span><span class="n">number_of_nodes</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
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<span class="k">if</span> <span class="n">settings</span><span class="o">.</span><span class="n">network_type</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span>
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<span class="n">G</span> <span class="o">=</span> <span class="n">nx</span><span class="o">.</span><span class="n">margulis_gabber_galil_graph</span><span class="p">(</span><span class="n">settings</span><span class="o">.</span><span class="n">number_of_nodes</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
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<span class="c1"># More types of networks can be added here</span>
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</pre></div>
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</div>
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</div>
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<div class="section" id="models-settings">
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<h2>Models Settings<a class="headerlink" href="#models-settings" title="Permalink to this headline">¶</a></h2>
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<p>After having configured the simulation, the next step is setting up the variables of the models.
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For this, you will need to modify the Simulation Settings JSON file.</p>
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<div class="code json highlight-default"><div class="highlight"><pre><span></span><span class="p">{</span>
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<span class="s2">"agent"</span><span class="p">:</span> <span class="p">[</span><span class="s2">"SISaModel"</span><span class="p">,</span><span class="s2">"ControlModelM2"</span><span class="p">],</span>
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<span class="s2">"neutral_discontent_spon_prob"</span><span class="p">:</span> <span class="mf">0.04</span><span class="p">,</span>
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<span class="s2">"neutral_discontent_infected_prob"</span><span class="p">:</span> <span class="mf">0.04</span><span class="p">,</span>
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<span class="s2">"neutral_content_spon_prob"</span><span class="p">:</span> <span class="mf">0.18</span><span class="p">,</span>
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<span class="s2">"neutral_content_infected_prob"</span><span class="p">:</span> <span class="mf">0.02</span><span class="p">,</span>
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<span class="s2">"discontent_neutral"</span><span class="p">:</span> <span class="mf">0.13</span><span class="p">,</span>
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<span class="s2">"discontent_content"</span><span class="p">:</span> <span class="mf">0.07</span><span class="p">,</span>
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<span class="s2">"variance_d_c"</span><span class="p">:</span> <span class="mf">0.02</span><span class="p">,</span>
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<span class="s2">"content_discontent"</span><span class="p">:</span> <span class="mf">0.009</span><span class="p">,</span>
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<span class="s2">"variance_c_d"</span><span class="p">:</span> <span class="mf">0.003</span><span class="p">,</span>
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<span class="s2">"content_neutral"</span><span class="p">:</span> <span class="mf">0.088</span><span class="p">,</span>
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<span class="s2">"standard_variance"</span><span class="p">:</span> <span class="mf">0.055</span><span class="p">,</span>
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<span class="s2">"prob_neutral_making_denier"</span><span class="p">:</span> <span class="mf">0.035</span><span class="p">,</span>
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<span class="s2">"prob_infect"</span><span class="p">:</span> <span class="mf">0.075</span><span class="p">,</span>
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<span class="s2">"prob_cured_healing_infected"</span><span class="p">:</span> <span class="mf">0.035</span><span class="p">,</span>
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<span class="s2">"prob_cured_vaccinate_neutral"</span><span class="p">:</span> <span class="mf">0.035</span><span class="p">,</span>
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<span class="s2">"prob_vaccinated_healing_infected"</span><span class="p">:</span> <span class="mf">0.035</span><span class="p">,</span>
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<span class="s2">"prob_vaccinated_vaccinate_neutral"</span><span class="p">:</span> <span class="mf">0.035</span><span class="p">,</span>
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<span class="s2">"prob_generate_anti_rumor"</span><span class="p">:</span> <span class="mf">0.035</span>
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<span class="p">}</span>
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</pre></div>
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</div>
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<p>In this file you will define the different models you are going to simulate. You can simulate as many models
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as you want.</p>
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<p>After setting up the models, you have to initialize the parameters of each one. You will find the parameters needed
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in the documentation of each model.</p>
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<p>Parameter validation will fail if a required parameter without a default has not been provided.</p>
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</div>
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<div class="section" id="running-the-simulation">
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<h2>Running the Simulation<a class="headerlink" href="#running-the-simulation" title="Permalink to this headline">¶</a></h2>
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<p>After setting all the configuration, you will be able to run the simulation. All you need to do is execute:</p>
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<div class="code bash highlight-default"><div class="highlight"><pre><span></span><span class="n">python</span> <span class="n">soil</span><span class="o">.</span><span class="n">py</span>
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</pre></div>
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</div>
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<p>The simulation will return a dynamic graph .gexf file which could be visualized with
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<a class="reference external" href="https://gephi.org/users/download/">Gephi</a>.</p>
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<p>It will also return one .png picture for each model simulated.</p>
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</div>
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</div>
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<div class="sphinxsidebarwrapper">
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<h3><a href="index.html">Table Of Contents</a></h3>
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<ul>
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<li><a class="reference internal" href="#">Usage</a><ul>
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<li><a class="reference internal" href="#simulation-settings">Simulation Settings</a></li>
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<li><a class="reference internal" href="#network-types">Network Types</a></li>
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<li><a class="reference internal" href="#models-settings">Models Settings</a></li>
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<li><a class="reference internal" href="#running-the-simulation">Running the Simulation</a></li>
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</ul>
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</li>
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</ul>
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<div class="relations">
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<h3>Related Topics</h3>
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<ul>
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<li><a href="index.html">Documentation overview</a><ul>
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<li>Previous: <a href="installation.html" title="previous chapter">Installation</a></li>
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<li>Next: <a href="models.html" title="next chapter">Developing new models</a></li>
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</ul></li>
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